This file 06_ReadMe_Virtual_Unfolding_Code_Dataverse.txt was generated on 2020-11-10 by AMANDA GHASSAEI, HOLLY JACKSON, JANA DAMBROGIO and DANIEL STARZA SMITH. 

GENERAL INFORMATION

1. Title of Dataset: "06 Virtual Unfolding Code for Unlocking history article", https://doi.org/10.7910/DVN/VBWOI6, Harvard Dataverse. 

2. Author Information 
        A. Principal Investigators (Letterlocking) Contact Information
                Name: Jana Dambrogio and Daniel Starza Smith (Unlocking History)
                Institution: Massachusetts Institute of Technology and King’s College London
		Addresses: 77 Massachusetts Avenue, Building 14-0513, Cambridge, MA 02139, USA; and, English Department, King’s College London, Virginia Woolf Building 7.15, 22 Kingsway, London, WC2B 6LE, United Kingdom.
                Email: jld@mit.edu, daniel.s.smith@kcl.ac.uk 

        B.  Principal Investigators (Algorithm) Contact Information
		Name: Amanda Ghassaei, Holly Jackson, Erik Demaine, Martin Demaine
     		Institution: Massachusetts Institute of Technology
                Address: 77 Massachusetts Avenue, Cambridge, MA 02139, USA
		Email: amanda.ghassaei@cba.mit.edu, hjackson@mit.edu, edemaine@mit.edu, mdemaine@mit.edu  

        C. Principal Investigators (X-ray micro-tomography – XMT) Contact Information
                Name: Graham Davis and David Mills
                Institution: Queen Mary, University of London
                Address: Dentistry, Francis Bancroft Building, Mile End Campus, London E1 4NS
                Email: g.r.davis@qmul.ac.uk, d.mills@qmul.ac.uk 

        D. Principal Investigators (Signed, Sealed, and Undelivered research team) Contact Information
		Name: Rebekah Ahrendt
		Institution: Utrecht University, Department of Media and Culture Studies
		Address: Muntstraat 2A, 3512 EV Utrecht, The Netherlands
		Email: r.s.ahrendt@uu.nl 

		Name: Nadine Akkerman
		Institution: Leiden University, English Department and Leiden University Centre for the Arts in Society (LUCAS), Leiden, Faculty of Humanities / English Literature
		Address: Witte Singel Complex, P.N. van Eyckhof 4, 2311 BV Leiden, The Netherlands.
		Email: n.n.w.akkerman@hum.leidenuniv.nl 

		Name: David van der Linden
		Institution: Radboud University, Faculty of Arts, Department of History, Art History and Classics
		Address: PO Box 9103, 6500 HD Nijmegen, The Netherlands.
		Email: d.vanderlinden@let.ru.nl 

		Name: Jana Dambrogio and Daniel Starza Smith, details as above.

3. Date of data collection: 
2013-2020.

4. Geographic location of data collection: 
Cambridge, Massachusetts, United States of America.

5. Information about funding sources that supported the collection of the data: 
The Signed, Sealed, and Undelivered project was supported by an Internationalization in the Humanities Grant from the Nederlandse Organisatie voor Wetenschappelijk Onderzoek (Dutch Research Council; project code 236-69-010); Metamorfoze; and Sound and Vision The Hague. Letterlocking research was supported by The Seaver Institute; MIT Libraries; the MIT Undergraduate Research Opportunity Program (UROP); The Gladys Krieble Delmas Foundation; The British Academy; The John Fell Fund at Oxford University Press; The Zilkha Fund at Lincoln College, University of Oxford; and three sources at King’s College London: the English Department; the International Collaboration Fund, Faculty of Arts and Humanities; and the King’s Undergraduate Research Fellow (KURF) scheme. Algorithm research received support from Adobe Research and sponsors of the MIT Centre for Bits and Atoms. 


SHARING/ACCESS INFORMATION

1. Licenses/restrictions placed on the data: 
Letterlocking instructional resources can be accessed for non-commercial use under a Creative Commons Attribution–NonCommercial 3.0 License. Permission for commercial use must be sought from the Unlocking History Research Group. 
Copyright © 2021-01-28 MASSACHUSETTS INSTITUTE OF TECHNOLOGY. Licensed under a Creative Commons Attribution 4.0 International License except where otherwise noted.

2. Links to publications that cite or use the data: 
https://rdcu.be/cf4jH

3. Links to other publicly accessible locations of the data: 
N/a.

4. Links/relationships to ancillary data sets: 
This data is part of the Dataverse “Unlocking history through automated virtual unfolding of sealed documents imaged by X-ray microtomography,” which contains other datasets related to the findings in that article: https://dataverse.harvard.edu/dataverse/uharticle . 

5. Was data derived from another source? 
No.

6. Recommended citation for this dataset: 
Dambrogio, Jana; Starza Smith, Daniel; Ghassaei, Amanda; Jackson, Holly; Demaine, Erik; Demaine, Martin; Davis, Graham; Mills, David; Ahrendt, Rebekah; Akkeman, Nadine; van der Linden, David, 2020, "06 Virtual Unfolding Code for Unlocking history article", https://doi.org/10.7910/DVN/VBWOI6, Harvard Dataverse. 


DATA & FILE OVERVIEW

1. File/Dataset List: 
* See Github: https://github.com/UnlockingHistory/virtual-unfolding
* File. 06_ReadMe_Virtual_Unfolding_Code_Dataverse.txt 

2. Relationship between files, if important: 
N/a.

3. Additional related data collected that was not included in the current data package: 
Follow this DOI link https://doi.org/10.7910/DVN/VBWOI6 to access up-to-date screen reader and description instructions related to this document at Harvard Dataverse. 

4. Are there multiple versions of the dataset? 
No.
        

METHODOLOGICAL INFORMATION

1. Description of methods used for collection/generation of data:
Please see Dambrogio, Ghassaei, Smith, Jackson et al, Unlocking history through automated virtual unfolding of sealed documents imaged by X-ray microtomography, Nature Communications.

2. Methods for processing the data: 
N/a.

3. Instrument- or software-specific information needed to interpret the data: 
N/a.

4. Standards and calibration information, if appropriate: 
N/a.

5. Environmental/experimental conditions: 
N/a.

6. Describe any quality-assurance procedures performed on the data: 
N/a.

7. People involved with sample collection, processing, analysis and/or submission: 
Source code generated by Amanda Ghassaei, Holly Jackson, Erik Demaine, and Martin Demaine.
ReadME file edited by Laura Bergemann.